2 papers
cs.LG2026
Observation-dependent Bayesian active learning via input-warped Gaussian processes
Sanna Jarl, Maria Bånkestad, Jonathan J. S. Scragg +1
Bayesian active learning relies on the precise quantification of predictive uncertainty to explore unknown function landscapes. While Gaussian process surrogates are the standard f…
cs.LG2025
Machine learning for in-situ composition mapping in a self-driving magnetron sputtering system
Sanna Jarl, Jens Sjölund, Robert J. W. Frost +2
Self-driving labs (SDLs), employing automation and machine learning (ML) to accelerate experimental procedures, have enormous potential in the discovery of new materials. However,…